• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.297-300
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• 2006

카오스 로봇의 하드웨어 구현에서 로봇의 차제 또는 바퀴가 정확하기 자기 위치를 인식하고 지시한 방향과 거리만큼 이동하는 것이 가장 중요하다. 본 논문에서는 방위 측정용으로 사용한 마그네틱 자이로센서를 대체한 새로운 각속도 센서를 사용하여 자기 위치 보정 능력 을 향상시키고 정확한 방향을 움직일 수 있는 카오스 로봇을 설계하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.2 s.173
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• pp.481-488
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• 2000

This paper presents a new passive gravity -compensating system for articulated robot manipulators. The system, which consists of linear zero- free -length springs, achieves exact counterbalancing o f the gravitational loads throughout the entire range of the manipulator workspace, A basic concept is to design springs such that the total potential energy of the system including the manipulator and the springs should be maintained constant. A prototype has been developed for a direct-drive five-bar manipulator and its performances have been investigated. Results show that the gravity-induced motor torques have been reduced to less than 5% of those of uncompensated robots. Also, the gravity-compensating system simplifies the position control algorithm while maintaining the trajectory-tracking errors in a satisfactory level. In conclusion, the proposed system efficiently improves the manipulator performances by reducing the driving motor size and the energy consumption as well as by simplifying the control systems.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.13-19
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• 1995

A dual purpose robot automation system is developed for both arc welding and spot welding by one robot within a cell. The need for automation of both arc welding and spot welding processes is urgent while the production volume is not so big as to accommodate separate stations for the two processes. Also, space is too narrow for separate stations to be settled down in the factory. A spot welding robot is chosen and the functions for arc welding are implemented in-house at cost of advanced functions. For the spot welding, a single pole type gun is used and the robot has to push down the plate to be wolded, which causes the robot positioning error. Therefore, position error compensation algorithm is developed. The basic functions for the arc welding processes are implemented using the digital I/O board of robot controller, PLC, and A/D conversion PCB. The weaving pattern is taught in meticulously by manual teach. A fixture unit is also developed for dual purpose. The main aspects of the system is presented in this paper especially in the design and implementation procedure. The signal diagrams and sequence logic diagrams are also included. The outcome of the dual purpose welding cell is the increased productivity and good production stability which is indispensable for production volume prediction. Also, it leads to reduction of manufacturing lead time.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.733-740
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• 2016

To achieve bipedal walking in real human environments, a bipedal robot should be capable of modifiable walking both on uneven terrain with different heights and on flat terrain. In this paper, a novel walking pattern generator based on a 3-D linear inverted pendulum model (LIPM) is proposed to achieve this objective. By adopting a zero moment point (ZMP) variation scheme in real time, it is possible to change the center-of-mass (COM) position and the velocity of the 3-D LIPM throughout the single support phase. Consequently, the proposed method offers the ability to generate a modifiable pattern for walking on uneven terrain without the necessity for any extra footsteps to adjust the COM motion. In addition, a control strategy for bipedal walking on uneven terrain with unknown height is developed. The torques and ground reaction force are measured through force-sensing resisters (FSRs) on each foot and the foot of the robot is modeled as three virtual spring-damper models for the disturbance compensation. The methods for generating the foot and vertical COM of 3-D LIPM trajectories are proposed to achieve modifiable bipedal walking on uneven terrain without any information regarding the height of the terrain. The effectiveness of the proposed method is confirmed through dynamic simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1256-1263
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• 2004

Output feedback passivation problem is studied when the given system is not minimum-phase or does not have relative degree one. Using a parallel connection with an additional dynamics, the authors provide a dynamic output feedback control law which renders the composite system passive. Sufficient conditions are presented under which the composite system is output feedback passive. As an application of the dynamic passivation scheme, a point-to-point control law for a flexible joint robot is presented when only the position measurements are available. This provides an alternative way of replacing the role of the velocity measurements for the proportional-derivative (PD) feedback law. The performance of the proposed control law is illustrated in the simulation studies of a manipulator with three revolute elastic joints.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.172-178
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• 1993

This paper deals with the modeling and experiment of a robot system for force/impact control performance. The basic model is composed of a direct drive motor, servo amplifier, link, force sensor and environments. Based on the developed model, the stability of the whole system was analyzed via root locus method. For the force control, integral force compensation with velocity feedback method shows the best performance of all the explicit force control strategies. In dealing with impact, PID position control and the explicit force control method were implemented. Instead of add more damping to the robot system by velocity feedback, we developed a new passive damping method and it was also applied to enhance the damping characteristic of the system.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.256-259
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• 1987

In this paper, a servo controller for a robot manipulator is developed. It consists of a conventional MRAS controller for each joint together with a feedback control to Dynamics compensation. To generale the control torque effectively a currant drive method is adopted. The speed of the actuator is measured by using a tachometer and the position of the link is measured by using a potentiometer. To show the effectiveness of the proposed control algorithm the proposed controller is tested in real time.